作者: Sarah M. Zala , Doris Reitschmidt , Anton Noll , Peter Balazs , Dustin J. Penn
DOI: 10.1371/JOURNAL.PONE.0181200
关键词: Speech recognition 、 Ultrasonic sensor 、 Gold standard (test) 、 Computer science 、 Bioacoustics 、 Detector
摘要: House mice (Mus musculus) emit complex ultrasonic vocalizations (USVs) during social and sexual interactions, which have features similar to bird song (i.e., they are composed of several different types syllables, uttered in succession over time form a pattern sequences). Manually processing vocalization data is time-consuming potentially subjective, therefore, we developed an algorithm that automatically detects mouse (Automatic Mouse Ultrasound Detector or A-MUD). A-MUD script runs on STx acoustic software (S_TOOLS-STx version 4.2.2), free for scientific use. This improved the efficiency USV files, as it was 4-12 times faster than manual segmentation, depending upon size file. We evaluated error rates using manually segmented sound files 'gold standard' reference, compared them commercially available program. had lower commercial software, detected significantly more correct positives, fewer false positives negatives. The errors generated by were mainly negatives, rather positives. study first systematically compare automatic detection methods, subsequent versions will be made community.